Grain Refinement of Magnesium Alloys by CONFORM: A Continuous Severe Plastic Deformation Route?
Bibliographic record
Abstract
Effective grain refinement through equal channel angular pressing (ECAP) for magnesium (Mg) alloys has been demonstrated by many researchers. Although with the capability to achieve superplasticity, the batch mode nature of this method and the required repetitive processing to attain ultrafine grained structure have prohibited it from being widely used in large-scale industrial production. In this study, a well-established metal forming method – the continuous extrusion forming (CONFORM) process – was employed as a severe plastic deformation route to refine the microstructure of Mg alloys. Cast Mg-3%Al-1%Zn (AZ31) rods were used as the feedstock and the cast structure (grain size of ~150 microns) was refined to ~1 micron after one pass CONFORM extrusion. Uniaxial tensile tests of the as-extruded samples were conducted at a temperature of 473K and an elongation of ~200% was achieved under a strain rate of 1×10-4 s-1. The significant grain refinement effect was attributed to the severe shear deformation occurred during the CONFORM process, which is very similar to ECAP but with even higher effective strains. The most important advantage of CONFORM over ECAP is that the former is a continuous route, so it is able to produce long products. It was also shown that CONFORM could be an additional forming method for Mg alloys to conventional rolling, forging and extrusion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".